We maximize product availability with minimal cashflow investment in 1/10 of the time. We solve a real problem for SMEs. With AI.

VOIDS is the leading forecasting and inventory management software solution for D2C brands. The VOIDS platform automates accurate product-level demand forecasting to proactively identify risks such as inventory inefficiencies (e.g., out-of-stocks) and take recommended actions to eliminate them before they occur. We help e-commerce brands achieve 98% inventory efficiency, 20x ROI, and six-figure cash profits in a matter of weeks. 50+ success stories, including FC Bayern, 6pm, Rosental, and Blackroll confirm this. Since our product launch in June 2023, we’ve achieved approximately 300% growth over the past year, and we’re now positioned to double our ARR by the end of 2025.

At VOIDS, you'll find a game-changing personal growth opportunity if you are driven, fast-paced, and passionate about challenging the status quo. Embrace the opportunity to take direct ownership of scaling our AI platform's success. Work alongside the team and co-founders Jannik and Tobias, who bring a wealth of experience in e-commerce growth and AI-based demand forecasting.

🛠 What you'll do

As a Senior Data Scientist – Demand Forecasting, you’ll own the core of our product: the VOIDS demand forecasting engine that currently forecasts €1,000,000,000 € of yearly revenue for our customers. Your mission is to solve our toughest challenge—developing and continuously improving a scalable forecasting solution capable of accurately predicting demand for diverse e-commerce customers. You'll thrive in complexity, handling varied and dynamic datasets, numerous input variables, shifting market behaviors, and volatile trends. Specifically, you will:

• Lead development of the forecasting engine that fuels VOIDS demand forecasting services, directly influencing customer outcomes and satisfaction
• Design and implement scalable forecasting methodologies adaptable to a diverse customer base and unique datasets
• Actively engage with customers, gathering deep insights and feedback to ensure our forecasting solutions meet their evolving needs
• Collaborate closely with the CTO, CEO, customer success, and engineers
• Identify and execute strategic improvements in scalability, accuracy, and performance of forecasting systems
• Enhance developer experience, advocating best practices, and upgrading tooling within the data science and engineering teams
• Actually get things done, deciding yourself what to focus on — without bureaucracy

✅ Must-Have Skills

• Fluent English communication skills; German is a plus
• Clear, professional, and asynchronous communication abilities
• 5+ years of Data Science experience, including at least 2 years specifically in time series forecasting (preferably consumer products)
• Proven 3+ years of Python experience, focusing on data science libraries such as NumPy, Pandas, Polars, scikit-learn, PyTorch, XGBoost, statsmodels, etc.
• Practical 2+ years of experience with forecasting methodologies and tools such as Nixtla, Darts, statsmodels, sktime, etc.
• Experience building and maintaining pipelines and APIs for model training/inference, using tools such as Airflow, AWS Sagemaker, MLflow, etc.
• Hands-on experience with SQL databases, ideally PostgreSQL
• Strong product intuition and a proactive, ownership-oriented mindset
• Demonstrated ability to ship and continuously enhance meaningful features
• Comfort with ambiguity and autonomy in problem-solving

🌟 Bonus / Nice-to-Have

• Experience with eCommerce and/or B2B SaaS startups
• Background in data engineering for scalable data pipelines, to cover the whole data pipeline more full-stack
• Familiarity with infrastructure frameworks (Terraform, Kubernetes, etc.)
• Exposure to technologies for handling larger data sets such as BigQuery, Spark etc.
• Contributions to developer experience and internal tooling improvements

🧱 Tech Stack

• Programming: Python (Pandas, Polars), SQL
• Modeling: Statistical, ML, and neural time series models (mostly Nixtla)
• Data Storage: PostgreSQL, AWS S3 (Parquet)
• ML Infrastructure: AWS SageMaker, AWS Lambda, MLflow
• Orchestration: Airflow on AWS
• Collaboration & AI Tools: GitHub Copilot, ChatGPT
• Containerization: Kubernetes (Airbyte hosting)

🎯 What Success Looks Like (First 3 Months)

• You’ve gained a solid understanding of the product and the data behind it
• You’ve shipped a larger feature / improvement that’s already in customers’ hands
• You’ve found and delivered a technical improvement that made dev or user life better
• You’ve built first relationships with customers that boost feedback cycles
• Everyone in the team knows what you are doing, and you proactively support others

🤖 How We Work

• AI-driven productivity: We actively leverage Copilot, GPT-4, and other AI tools.
• Fast-paced, high-impact, no overhead: Short daily stand-ups (15min), efficient weekly planning (30min), autonomous decisions, ship daily
• Engineering culture & values: pragmatism, simplicity, maintainability & customer focused
• 50/50 Hybrid flexibility: Mix remote work with our inspiring office in Hamburgs city center
• Continuous learning: We trust your expertise, value your ideas, and encourage proactive growth
• Autonomous decision making: We trust engineers to own their work and loop others in when needed, typically there is only lightweight consultation with the CTO and engineers

🎁 What You’ll Get

• Permanent full-time contract (no B2B)
• Competitive salary (€90,000–€110,000)
• Equity available for senior hires
• 30 days paid vacation
• New Mac Book Pro & min. 2 Monitors in the office ;)
• Regular team events and quarterly off-sites
• Real ownership and influence
• A calm, focused work environment that rewards initiative
• Wellpass membership to unlimited fitness, yoga, swimming, climbing, and more

🧑‍🏫 Hiring Proce

ssWe move fast and keep it simpl

• e.Initial Screening (30 mi
• n)Technical Interview with CTO (30 mi
• n)Realistic Live Coding Challenge (90 mi
• n)Meet the Team in Hambu
• rgOffer within 2 weeks from start to decisi

👉 Apply here or send us your answers and your CV: jobs@voids.